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Functional programming languages for AI problem solving

Published online by Cambridge University Press:  07 July 2009

Eleanor Bradley
Affiliation:
Artificial Intelligence Applications institute, University of Edinburgh, UK

Abstract

Many problem domains exhibit inherent parallelism, and parallel systems which capture and exploit this can be used to look for efficient solutions to AI problems. Functional programming languages are expected to be efficiently realisable on fifth generation hardware. A rational reconstruction of AI programming paradigms is used to investigate the programmability and performance of functional languages in this particular area.

Three languages—Standard ML, Hope+ and Miranda—are used in the rational reconstruction, each language being used to implement three applications. Results indicate that functional programming languages have become much more useable in recent years, and have the potential to become useful tools in AI problem solving. A brief annotated bibliography of texts which covers the introduction to, theory and implementation issues of, functional programming languages, is included.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1991

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